Spotting consumer behavior changes in your SEO data

If you look deeply, you can actually understand a lot of consumer behavior in your SEO data.

Last week, I published an article on G2 about our stunning traffic spike due to remote work. We hit all-time traffic records and saw some of our categories increase by over 500%.

This week, we’re seeing even more traffic. Products like Zoom, Skype, Slack are the expected winners. But we also see tons of whiteboard software, telemedicine, VPN, e-signature, e-notary, and tons of other tools win.

One part of the trend is the consumerization of B2B software. Software that was previously used when working from home is now used in our everyday lives. Why not use Zoom, Skype, or Hangouts for family calls, classes, and other things?

It fits surging online fitness, yoga, and meditation classes. We order much more online, consume more news, and play more to keep ourselves busy.

What categories see drops in usage?

Restaurants

Events

Flights

Vacation/travel

Lodging

Some drops are pretty dramatic and will likely lead to layoffs and brands going under.

What we can do

One thing is important for us marketers to keep in mind: we don’t know how things will turn out.

One of the biggest mistakes I learned not to make in recessions and other crises is thinking you know what will happen.

Instead, keep a pulse on the data, stay humble, and look for opportunities. We need to increase how often we look at data points and how many we look at. That’s the only way to understand what is happening right now and that’s what we can react to and use to forge plans.

To make this a bit more concrete: we need to keep an eye on search volume and impressions for queries that are important for the business or could become more important.

Here’s how:

1. Create a new report in Google Data Studio with the Search Console connector and Site Impressions.

2. Create a table with the dimension “query” and the metrics average position, clicks, and impressions.

3. Look for queries that had no (or hardly any) change in average position but big changes in impressions. Those are keywords that most likely experience a change in consumer behavior.

See below what the table should look like. Notice the two keywords in this sample data with unchanged positions but declining impressions.

The same could work the other way round with queries that have stable positions but gain in impressions.

You could also use Google Trends with the Strategiq Google Trends connector or Python.

Remember: your goal is to get a pulse on what’s increasing and decreasing to find opportunities.